|T F |2. |Pearson’s correlation coefficient, r, does not depend on the units of measurement of the two variables. |
|T F |3. |The value of Pearson's r is always between 0 and 1. |
|T F |4. |If r is close to 1, then the points lie close to a straight line with a positive slope. |
|T F |5. |The slope of the least squares line is the average amount by which y increases as x increases by one unit. |
|T F |6. |The least squares line passes through the point[pic]. |
|T F |7. |The slopes of the least squares lines for predicting y from x, and the least squares line for predicting x |
| | |from y, are equal. |
|T F |8. |The higher the value of the coefficient of determination, the greater the evidence for a causal relationship |
| | |between x and y. |
|T F |9. |The coefficient of determination is equal to the positive square root of Pearson's r. |
| | | |
| | |10. The data below were gathered on a random sample of 5 basking sharks, swimming through the water and filter-feeding, i.e. |
| | |letting the water bring food into their mouths. |
| | |Mean speeds for